Object Orientation Corrected Bounding Box Fit for Point Cloud Clusters.

• Apollo's Min-box Object Builder
• TAS: An Orientation Corrected Bounding Box Fit Based on the Convex Hull under Real Time Constraints, similar to Apollo, IV 2018.
• M. Himmelsbach's Fit Oriented Box by a RANSAC algorithm to fit the dominant line in the xy-projection of the segment’s points; the other axis is then taken to be perpendicular to the dominant line, IV 2012.

  @inproceedings{himmelsbach2012tracking,
    title={Tracking and classification of arbitrary objects with bottom-up/top-down detection},
    author={Himmelsbach, Michael and Wuensche, H-J},
    booktitle={Intelligent Vehicles Symposium (IV), 2012 IEEE},
    pages={577--582},
    year={2012},
    organization={IEEE}
  }

1. git clone as a ROS package, with common_lib as dependency.
2. find_package for this object_builders_lib local package.

   find_package(catkin REQUIRED COMPONENTS
       # ROS core
       roscpp
       # ROS messages
       #std_msgs
       #sensor_msgs
       # ROS PCL
       #pcl_conversions
       #pcl_ros
       # 3rd modules for ROS, like Eigen
       cmake_modules
       # local packages
       common_lib
       object_builders_lib
   )

3. Use Point Cloud Clusters' Object Builder in your source code.

   // 1.include files
   #include "object_builders/base_object_builder.hpp"
   #include "object_builders/object_builder_manager.hpp"
   
   // 2.define object builder
   boost::shared_ptr<object_builder::BaseObjectBuilder> object_builder_;
   
   // 3.create object builder by manager
   object_builder_ = object_builder::createObjectBuilder();
   
   // 4.build 3D orientation bounding box for clustering point cloud
   std::vector<PointICloudPtr> cloud_clusters;
   std::vector<ObjectPtr> objects;
   object_builder_->build(cloud_clusters, &objects);